Value Gain-based Power Line Subcarrier Aggregation Method under Colored Noise

With the large-scale power electronic equipment connected to the distribution network in the form of a new power system, the colored noise generated by power equipment will greatly reduce the efficiency of data transmission. The power line communication subcarrier grouping aggregation method features high transmission efficiency, excellent reliability, and high stability, which can improve the anti-interference and anti-noise performance of power line subcarriers. However, traditional subcarrier packet aggregation methods neglect the network topology changes and node service requirements, resulting in low adaptability of available subcarriers for power electronics scenarios. Therefore, we propose a value gain-based power line subcarrier aggregation method under colored noise. It can achieve adaptive colored noise awareness and dynamically optimize the subcarrier grouping aggregation. Simulation results demonstrate the excellent performance of the proposed algorithm in terms of availability and utilization efficiency.


Introduction
With the continuous promotion of the development of new power systems, massively distributed energy sources access to the distribution network, and various types of electrical equipment have increased sharply [1][2].However, the power electronic devices in various electrical equipment generate a lot of colored noise, which will interfere with the normal communication between devices in the power line communication network [3].Power line subcarrier aggregation technology has the advantages of safety, stability, economy, and reliability.It can effectively avoid the co-frequency interference of electronic devices, reduce the impact of colored noise, as well as ensure stable and efficient data transmission of the power line communication network [4].It is widely used in power resource scheduling, electrical equipment detection, mobility management, and other fields [5].
However, traditional methods of subcarrier determination and aggregation based on the reliability factor face the following problems [6].On the one hand, the colored noise and topology of the power communication network are constantly changing, and the traditional methods cannot select the appropriate subcarriers according to the changing rules.On the other hand, traditional methods do not consider the importance of the communication node carrying services and the characteristics of the node data flow, resulting in insufficient adaptability of network resources and node requirements.
A value gain-based power line subcarrier aggregation method under colored noise is designed in this paper to provide a solution.This method determines the available subcarriers in each packet by comparing the Signal to Topology and Noise Ratio (STNR) change time sequence of each subcarrier.It selects the subcarrier packet with the largest value gain through the calculation to avoid the frequent reconstruction of network subcarrier aggregation.The proposed method can meet the differentiated requirement of each communication node, which is conducive to stable and efficient data transmission in the power line communication network.
For this paper, the remaining organization is as follows.Section 2 briefly introduces the hierarchical and hierarchical networking architecture of power line carriers with colored noise.In Section 3, a value gain-based power line subcarrier aggregation method under colored noise is proposed.Section 4 shows the simulation results.Section 5 summarizes this paper.

Hierarchical and Hierarchical Networking architecture of Power Line Carrier with Colored Noise
The hierarchical and hierarchical networking architecture of a power line carrier with colored noise consists of a Communications Control Officer (CCO), multiple Points of Control and Observation (PCO), and multiple Stations (STA), which is shown in Figure 1.The whole network is divided into four layers [7][8][9].CCO is located at the top of the whole architecture, responsible for coordinating and managing subordinate nodes and providing transmission functions for subordinate communication networks.The remaining three layers are composed of a hybrid deployment of PCO and STA.Among them, PCO is connected to CCO and usually consists of two first-in, first-out queues.Its function is similar to a pair of input and output ports, which send commands to one end of the queue and receive response signals from the other end of the same queue.STA refers to each terminal device connected to the communication network, which can be connected to CCO or PCO.PCO or the combination of CCO and corresponding STA can be considered as a group.This networking architecture has the characteristics of independent networking, selforganization, and multi-hop routing, which is conducive to accurately and orderly obtaining noise information in each power line communication group.
Considering the various electrical equipment in the hierarchical network architecture of the power communication network [10], each group composed of PCO or CCO and corresponding STA will be affected by the color noise and topology changes of the power line communication network.This article selects the available subcarriers between each STA and the upper layer PCO or CCO in each group based on the noise type, noise power, network topology change rate, and network noise change rate of the subcarriers.Based on the changes in STNR after subcarrier allocation, delay reduction rate, packet loss rate reduction rate, node carrying business importance, node data flow characteristics, and the current number of available subcarriers of the node, all subcarriers are grouped to achieve group aggregation of power line subcarriers that adapt to color noise in a high proportion of power electronic access scenarios.

Colored Noise Model
Sensing the current power line communication network topology grouping, and there are M groupings, the set is  .

Available Subcarriers Model
STNR (Signal to Topology and Noise Ratio) is a parameter used to judge the availability of subcarriers.The availability of subcarriers with large noise impact and complex topology is small.In the t -th iteration, STNR of the subcarrier i s in group m g is given by: , , , where , ( ) W t represents the transmission power of subcarrier i s . ( )t  represents the topology changing rate of the network.p and l represent the weight of noise type and power of subcarriers, respectively., ( ) represents the gain signal-to-noise ratio, which is given by 2 , , , where e P represents the target bit error rate.
  The


, it is an available subcarrier.

Value Gain-based Subcarrier Packet Aggregation Optimization
The subcarrier i s is assigned to the group m g , and the value gain is calculated, which is given by: where , ( ) and , ( ) G t represent the delay reduction rate, the decrease of packet loss rate, and the importance of carried services, respectively.
, ( ) J t and   K t represent the mean value of data traffic, the probability of traffic burst, and the number of available subcarriers, respectively. ,  ,  ,  ,  ,  , and  are the weight parameter of corresponding indicators.

 
, , all available subcarriers are assigned to the group with the highest value gain.The above steps are repeated until all subcarrier groupings are completed.The proposed algorithm is depicted in Figure 2.

Simulation Results
This paper considers a power line communication subcarrier packet aggregation scenario with 1 CCO, 3 PCOs, and 9 STAs.0  is set to -114 dBm.According to the importance of each indicator to the value gain,  ,  ,  , and  are set to 5,  ,  ,  , and  are set to 10.The proposed algorithm is compared with no value gain subcarrier packet aggregation optimization algorithm (NVG-SPA) [11] and the random subcarrier packet aggregation optimization algorithm (R-SPA) [12].NVG-SPA does not consider the gain value and network topology changes when optimizing subcarrier packet aggregation.R-SPA just randomly optimizes subcarrier packet aggregation., compared with NVG-SPA and R-SPA, the proposed algorithm increases the number of available subcarriers by 41.01% and 81.57%.This is because the proposed algorithm can calculate the STNR in each iteration and determine the number of available subcarriers by comparing it with the threshold value.NVG-SPA and R-SPA cannot be aware of the change of network topology between iterations, so they cannot identify the available subcarriers, resulting in fewer available subcarriers.

Conclusion
Aiming at the problem of low adaptability of available subcarriers to electronic power scenarios, a value gain-based power line subcarrier aggregation method under colored noise is proposed.It significantly reduces the impact of colored noise and other interference factors, thereby improving the reliability of data transmission in the PLC network.
Compared with NVG-SPA and R-SPA, the number of available subcarriers of the proposed algorithm is increased by 41.01% and 81.57%, and the subcarrier utilization efficiency is increased by 35.06% and 55.67%, respectively.We will study the neural network enhanced interference cancellation based on power line carrier aggregation to further improve the data transmission efficiency of the power line communication network.

Figure 1 .
Figure 1.Hierarchical and hierarchical networking architecture of power line carrier with colored noise.

Figure 2 .
Figure 2. The flowchart of value gain-based power line subcarrier aggregation method.

Figure 3
Figure 3 shows the number of available subcarriers versus iterations.When 200 t 

Figure 4 .
Figure 4. Subcarrier utilization efficiency of three algorithms Figure 4 shows the subcarrier utilization efficiency of three algorithms.Compared with NVG-SPA and R-SPA, the proposed algorithm increases the subcarrier utilization efficiency by 35.06% and 55.67%.This is because the proposed algorithm can effectively select the optimal subcarrier by judging the gain value composed of multiple indicators, which avoids frequent reconstruction of network subcarrier aggregation and improves the utilization rate of subcarriers.R-SPA has the worst carrier utilization because it only selects randomly and cannot avoid frequent reconstruction of network subcarrier aggregation.

.
. Multiple STAs are connected by a PCO or CCO in each group.In group m g , we assume that there are I subcarriers channels in total, the set of which is denoted as We partition the total duration of model training into T iterations, and the set is {1,..., ,..., } t T   .The Network topology changes once an iteration.The observed network colored noise of each subcarrier is compared with the noise library to determine the colored noise type and colored noise power.The noise type and power of subcarrier i s in group m g in the t -th iteration are defined as ,( ) set of STNR of the subcarrier